A variety of patient health ailments indicate continuous long-term monitoring of one or more types of physiologic activity. For example, many types of cardiac arrhythmia indicate ongoing monitoring of the patient's cardiac activity for indications that delivery of therapy is indicated. Sleep apnea is another health ailment where ongoing monitoring of the frequency and severity of occurrence of the condition is beneficial for improving the delivery of therapy and monitoring the progression of the condition. Cardiac arrhythmias can occur with symptoms that are not always readily observable or noticeable by the patient. As the name implies, sleep apnea occurs during sleep and patients suffering from this condition are also frequently unaware of the frequency and duration of occurrences of apneic episodes.
Thus, it is frequently preferable that a device or system be provided to the patient which automatically senses and monitors one or more physiologic processes related to the patient's health ailment to monitor conditions of which the patient may be unaware. As such conditions are frequently of a chronic nature indicating long term monitoring of the condition, it is preferable that such systems and devices for monitoring the condition be unobtrusive and convenient to employ for the patient. While external monitoring systems are quite useful and widely employed for short term use, such as for diagnosis or observation in a clinical setting, externally applied or worn appliances are generally disfavored by patients for the inconvenience to their bathing, dress, and other normal day-to-day activities. Thus, in many applications indicating long term monitoring of one or more physiologic processes, an implantable device which minimally interferes with the patient's bathing, clothing, etc. is often preferred. Such implantable devices are generally powered by long life batteries to extend the useful life of the device before battery replacement is required. Extended battery life is highly desirable as battery replacement requires an additional invasive surgical procedure.
A difficulty arises, however, with accurately sensing certain physiologic processes with a battery powered implantable device. In certain applications, a given physiologic activity may generate associated physical phenomena which can be referred to as signals corresponding to the underlying physiologic activity. Many types of physiologic activity generate signals which are of relatively low magnitude. For example, certain nerve activity may generate electrical signals on the order of one μV. Sensors, such as electrodes, can be applied to pick up these relatively low amplitude signals and convey these signals to appropriate amplifier and level detector circuits for further analysis. However, as the nerves are located within the patient's body cavity, other electrical signals arising from other physiologic activity is frequently communicated internally to the nerves or is otherwise or is otherwise detected by the sensors and constitutes noise.
Noise can be considered physical phenomena similar in nature to the signals which are of interest; however, the noise is of less or no interest in the sensing of the signals. Noise present in the sensing environment can confound the accurate sensing of the signals of interest. Noise is particularly troublesome when it has comparable or even greater magnitude and similar frequency characteristics or spectra as the signal of interest.
In one particular example, the phrenic nerves conduct electrochemical signals to the patient's diaphragm to drive the rhythmic contractions and relaxations of the diaphragm for the patient's cyclical respiration. The phrenic nerves generate electrical signals on the order of one μV. However, suitable preferred locations for placement of sensing electrodes on the phrenic nerves, such as adjacent the inferior vena cava (IVC) or the superior vena cava (SVC) are also adjacent the patient's heart. The cyclical depolarizations of the heart muscle create myopotentials that are on the order of one millivolt or more, e.g., of a thousand times or more greater magnitude than the phrenic nerve signal activity. The frequency spectra of the cardiac myopotentials are also comparable and overlapping to the nerve signals. Thus, accurately sensing from the phrenic nerves on an extended long term basis when it is not feasible to surgically expose and isolate the nerves is particularly challenging as the sensing environment is repeatedly exposed to noise that is many orders of magnitude greater than the actual signals of interest.
As the frequency spectra of the cardiac myopotentials is comparable and overlapping to that of the phrenic nerve signals, filtering techniques offer limited utility in suppressing the noise to accurately sense the nerve signals of interest. A variety of sophisticated signal recognition or detection algorithms are known, however, they are relatively demanding of computing capacity and generally require generally high rate sampling, on the order of 30 kHz or more. Implementing such relatively high rate sampling and executing sophisticated signal processing of algorithms is not generally feasible in an implantable device as the high sampling rate to implement such algorithms is too demanding of the limited battery power and would unacceptably shorten the useful life of the device.
Thus, it will be appreciated that there is an ongoing need for systems and devices capable of efficiently and accurately sensing relatively low magnitude signals of interest in a sensing environment which is exposed to relatively high magnitude noise of comparable and/or overlapping frequency spectra with the signals of interest. It would be a further advantage for such systems and devices to provide the desired improved performance in a relatively simple to implement and low cost manner. There is a particular need for systems and devices capable of supporting nerve sensing, including phrenic nerve sensing, on a long term in vivo or implantable basis, e.g. with a battery powered device.